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Suppose I have the following tables
Releases
ReleaseID |
A |
B |
C |
Tickets
TicketID | ReleaseID | Stuff |
1 | A | xyz1 |
1 | A | abc1 |
2 | B | xyz2 |
2 | B | abc2 |
3 | B | xyz3 |
4 | C | xyz4 |
Both tables are related in the data modell via the ReleaseID fields, i.e. the relation is 1:m from table Releases to table Tickets.
What I want is a calculated column in Releases that counts the unique occurences of TicketID in table Tickets associated with this ReleaseID. So the result should be
ReleaseID | RelatedTickets |
A | 1 |
B | 2 |
C | 1 |
I can probably do this with explicit DISTINCCOUNT, CALCULATE and FILTER combination. However I would like to make use of the relation of the tables. But I can't get my head around this. I found the DISTINCT COUNT pattern https://www.daxpatterns.com/distinct-count/ however this looks at the RELATED side of the relation, here I would be requiring the RELATEDTABLE side (I guess).
Thanks for any hints!
Solved! Go to Solution.
Hi @janitor048
You can add a column like
Column = CALCULATE( DISTINCTCOUNT( Tickets[TicketID] ) )
Or simply use a Measure
Measure = DISTINCTCOUNT( Tickets[TicketID] )
Hi @janitor048
You can add a column like
Column = CALCULATE( DISTINCTCOUNT( Tickets[TicketID] ) )
Or simply use a Measure
Measure = DISTINCTCOUNT( Tickets[TicketID] )
Just found this. Was having the same problem as the Janitor. The thing that I don't understand is why I don't have to use the RELATEDTABLE function. I thought that calculated columns disabled filter context. Why in this case does the calculated column apply the filter from the One table to the Many table?
Many thanks.
@Mariusz that was kind of easy. Don't know why I haven't stumbled across this solution myself. Probably I was too busy trying to somehow get RELATEDTABLE in there...
Thanks!
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